Avaliação de desempenho de web services orquestrados com BPEL4People - Holanda, Henrique Jorge Amorim (2012)
Web Services (WS) are pillars for the construction of service-oriented applications. A number of languages for web service composition have been proposed, formed a consensus on the language of business process execution (BPEL). BPEL focuses on business processes that orchestrate WS interactions. However, in general, business processes are composed of a broad spectrum of activities that often require human involvement to perform tasks, review or approve steps and enter data. These human interactions are discussed in a new specification of BPEL called BPEL4People. BPEL4People introduces human activity to BPEL. With the use of BPEL4People, formal models (such as Petri nets) of BPEL4People have been proposed. Based on formal models is possible to perform formal analysis, such as performance analysis of models to discover potential problems with the WS orchestrated with BPEL4People. There are two dimensions important to the performance of WS: response time and scalability. The response time is the ability of a system to provide an acceptable time for their activities and scalability is the ability of a system to continue to fulfill its goals of response time when demand for it increases. Some works have been proposed about the performance analysis of WS orchestrated with BPEL. In this thesi, it is proposed an architecture called ``SOASPE' (SOA + SPE) for the transformation of the BPEL4People code in generalized stochastic Petri nets (GSPN) and colored Petri nets (CPN). Through the GSPN and CPN models of BPEL4People is possible to evaluate the performance of WS orchestrated with BPEL4People by comparing their real response times when subjected to a number of requests and response times of the GSPN and CPN models generated by the architecture ``SOASPE' when simulations with the same amount of requests. During the transformation of BPEL4People code, Petri nets are used to model BPEL activities and human activities. Then, by simulation of generated models, potential problems with the performance of WS orchestrated with BPEL4People can be detected.